Multiscale assessment of habitat selection and avoidance of sympatric carnivores by the endangered ocelot

Habitat selection by animals is a complex, dynamic process that can vary across spatial and temporal scales. Understanding habitat selection is a vital component of managing endangered species. Ocelots (Leopardus pardalis), a medium-sized endangered felid, overlap in their northern range with bobcats (Lynx rufus) and coyotes (Canis latrans), with all three species sharing similar space and resource use. As the potential for competition between these three carnivores is high, understanding differences in habitat use and the effect of these potential competitors on habitat selection of ocelots is essential to conservation. Our objective was to compare habitat selection between species and examine if ocelots avoided areas used by competitors at broad and fine scales. We captured and collared 8 ocelots, 13 bobcats, and 5 coyotes on the East Foundation’s El Sauz Ranch and the Yturria San Francisco Ranch in South Texas, USA from 2017 to 2021. We compared 2nd (position of home range) and 3rd (use within the home range) order selection across species and examined whether ocelots avoided areas categorized as high probability of use by bobcats and coyotes across both orders of selection. We found a preference for heterogeneous landscapes by bobcats and coyotes while ocelots were strongly tied to woody cover across both orders. At the 2nd order, ocelots selected areas with higher probability of use by bobcats and showed no response to higher probability of use by coyotes, suggesting ocelots did not avoid either species. However, at the 3rd order, ocelots avoided areas used by coyotes. Ocelots selected for areas of use by bobcats at the 2nd order and 3rd order. Results suggest that at the broader scale, placement of the home range is not affected by the presence of sympatric carnivores, however, at a finer scale, ocelots are avoiding coyotes but not bobcats. Our study emphasizes the importance of woody and herbaceous cover at the broad scale and dense vegetation at the finer scale to sustain ocelots. In addition, we show differing patterns of interspecific avoidance by ocelots across species and scales.


Methods
Animal capture. We captured 6 ocelots (2 male, 4 female), 12 bobcats (6 male, 6 female), and 5 coyotes (2 male, 3 female) on the El Sauz Ranch and 2 ocelots (1 male, 1 female) and 1 male bobcat on the Yturria Family's San Francisco Ranch from January 2017 to May 2021. All captured individuals were adults. Animals were captured using single-door Tomahawk box traps (108 × 55 × 40 cm: Tomahawk Trap Co., Tomahawk, WI, USA). We set up to 20 stations of 1-2 box traps each across one to two trap lines in mixed and dense thornshrub and live oak forest on each property from November to May each trapping season. The number of traps varied throughout each season; dependent on weather and personnel availability. We baited the box traps with a live chicken (Gallus gallus), or pigeon (Columbia livia) separately contained within a compartment inaccessible from the trap 30,31 . We immobilized captured animals using a 4:1 mixture of tiletamine hydrochloride and zolazepam hydrochloride (Telazol™, Zoetis, Florham Park, NJ, USA) at a dose of 5 mg/kg in 2017 and used a mixture of ketamine hydrochloride (4-5 mg/kg) and medetomidine HCl (0.05 mg/kg) and a reversal of 5 mg of atipamezole per 1 mg medetomidine (ZooPharm, Laramie, WY, USA) from 2019 to 2021 (no captures were conducted in 2018) 30,31,48 . Sedation protocols were changed following recommendations from our collaborating wildlife veterinarians. Each captured individual was fitted with a Lotek Minitrack and Litetrack global positioning system www.nature.com/scientificreports/ (GPS) satellite collar (Lotek™, New Market, ON, Canada). Collars were programmed to record locations every 30-60 min and to automatically drop after either 4-6 months or 1 year; longer fix schedules and drop-off times varied based on a concurrent study using these data . All capture and handling of wildlife were conducted following United States Fish and Wildlife Service permit (#PRT-676811), Texas Parks and Wildlife Department  permit (#SP0190-600), and Texas A&M University Kingsville Institutional Animal Care and Use Committee  protocol (2015-12-20B, 2019-2-28, 2020-8-28) and all methods were conducted in accordance with the relevant guidelines and regulations as well as in accordance with ARRIVE guidelines.
2nd order habitat selection. We estimated the home range of each collared individual using a 95% adaptive kernel density estimate (aKDE). To evaluate selection at the 2nd order, we compared the placement of the true home range with 50 random home ranges (Design III) 49 . We calculated the centroid of each aKDE and simulated the centroid of a random home range within the average dispersal distance for each species (Fig. 1). Dispersal distances used for this step were 7.7 km for male ocelots and 2.5 km for female ocelots 50 , 5.58 km for bobcats 51 , and 9.0 km for coyotes 52 . Dispersal distances of ocelots and bobcats were reported from South Texas. Dispersal of coyotes in South Texas has not been documented, to our knowledge, and the value used above was recorded in Utah (western United States). As no sex-specific values for dispersal were provided for bobcats and coyotes in South Texas, we elected to use the dispersal distance for both males and females. The centroid of each random home range was then buffered based on the size of the observed home range for each individual, resulting in 50 random, circular home ranges equal in area to the observed home range. Within each observed and random home range, we sampled locations at a rate of 100 points/km 2 to maintain consistent sampling density across individuals and species. We used unsupervised classified 2018 Landsat 8 imagery (30 m) developed by Lombardi et al. 30 for the study area to evaluate the influence of landscape structure of woody, bare ground (bare) and herbaceous cover types. Classified imagery (91.9% accuracy) was categorized into six land cover types: woody, herbaceous, agriculture, bare, urban development and water. Landscape metrics were then calculated using an 8-cell (Queen's rule) moving window analysis with a window size of 116 m (based on the average step length of ocelots) using FragStats 4.4 30,53 . We identified five metrics previously associated with habitat selection of the target species throughout their range 21,30,54 . For bare, herbaceous, and woody cover, we generated values of mean patch area (MPA; ha), landscape shape index (LSI [the ratio of the actual landscape edge length to the minimum possible edge length]), edge density (ED; m/ha), patch density (PD; patches/100 ha), and percent land cover (PLAND; %), totaling 15 variables. We calculated each raster at a 30 m resolution. All variables in the model were standardized by standard deviation.
We modeled habitat selection using mixed-effect logistic regression models with animal ID as a random intercept using the 'lme4' package in program R 55 . We evaluated a set of 12 candidate models using an AIC c model selection process 56,57 and considered models ∆AIC c < 2.0 as competing models. Models were created to represent differing hypotheses on the importance of cover type, fragmentation, and patch size while avoiding combinations with highly correlated variables (cor > 0.6). Top models, according to AIC c , for bobcats and coyotes were used to predict the probability of bobcat and coyote use across the landscape. These variables were then included in models of habitat selection for ocelots, to examine whether ocelots were avoiding bobcats and/or coyotes. To avoid issues with multicollinearity, we modified our list of candidate models to not include the probability of bobcats and/or coyotes in the same model with highly correlated variables and evaluated a list of 10 candidate models. Using the output of one model as a predictor variable in another model does not propagate uncertainty from one model to the next, however, we considered this information as useful to describe ocelot behavior and examine avoidance between species. 3rd order habitat selection. We examined selection at the 3rd order, within each individual's home range.
We maintained the same estimate of each individual's home range as used in the 2nd order comparison (95% aKDE). Selection at the second order was evaluated within a bounding area based on dispersal distance and position of random home ranges at a distance from the original, while third order selection was evaluated within each animals home range, thereby resulting in a smaller area examined. Within each home range, we randomly sampled 10 locations for each true location collected. At the third order, the variables considered were vegetation density (vegetation points/cell), percent canopy cover (%), distance (m) to open areas (< 25% canopy cover), distance (m) to dense cover (> 75% canopy cover), and patch shape (the ratio of the actual patch perimeter to the minimum possible perimeter) and area (m 2 ) of dense cover 31 . Vegetation density and canopy cover were obtained from light detection and ranging (LiDAR) data collected by the United States Geological Survey for South Texas in 2018 58 at 70 cm resolution. We classified LiDAR data and calculated landscape metrics in program LP360 (GeoCue, Madison, AL, USA). We calculated distance to open areas, distance to dense cover, and patch size and shape of dense cover from the LiDAR canopy cover raster. We calculated each raster at a resolution of 10 m. All variables in the model were scaled by standard deviation and centered. We evaluated selection using mixed-effect logistic regression models with animal ID as a random intercept. We evaluated a set of 12 candidate models using an AICc model selection and considered models ∆AIC c < 2.0 as competing models. These models represented differing hypotheses on the importance of vegetation structure and landscape composition while avoiding combinations of highly correlated variables (cor > 0.6). We calculated probability of bobcat and coyote use based on the top models based on AICc. These variables were included in the habitat selection models of ocelots. We also included 2nd order probability of bobcats and coyotes to examine if there was any avoidance occurring across scales of selection. To avoid issues with multicollinearity, we modified our list of candidate models for ocelots and evaluated a set of eight candidate models that included probability of bobcats and coyotes at the 2nd and 3rd order, distance to dense cover, vegetation density and patch area. www.nature.com/scientificreports/

Results
At the 2nd order, habitat selection of bobcats was best predicted by woody mean patch area (MPA), woody patch density (PD), herbaceous MPA, herbaceous edge density (ED), bare MPA, and bare ED (∆AIC c > 2.0;  Table 4). Habitat selection of coyotes was also best predicted by distance to dense cover, distance to open areas, canopy cover, and patch area (∆AIC c = 1.10; Table 3, Fig. 6). We elected not to average models with the second competing model as the predictor variables only differed by the substitution of vegetation density for canopy cover and these variables were highly correlated. Within their home range, coyotes selected areas closer to dense cover and open areas, such that a standard deviation increase in distance to dense cover and open areas was associated with a decrease in odds of use of 23.6% (OR = 0.76, 95% CI [0.74, 0.79]) and 31.6% (OR = 0.68, 95% CI [0.66, 0.70]) respectively, and selected larger patches of woody cover Table 1. AICc model selection describing 2nd order selection of bobcats (Lynx rufus), coyotes (Canis latrans) and ocelots (Leopardus pardalis) in South Texas, USA from 2017 to 2021. Top five models out of 12 candidate models are shown (10 in the case of ocelots). Variables include mean patch area (MPA; ha), landscape shape index (LSI [the ratio of the actual landscape edge length to the minimum possible edge length]), edge density (ED; m/ha), patch density (PD; patches/100 ha), and percent land cover (PLAND; %) for three cover types (bare, herbaceous and woody cover), and probability of bobcat and coyote 2nd order use in the case of ocelot habitat selection. All variables in the models were scaled and centered.  Table 4). Third order selection of ocelots was best predicted by distance to dense cover, patch area, vegetation density, probability of use by bobcats at the 2nd and 3rd order, and probability of use by coyotes at the 2nd and 3rd order (∆AIC c > 2.0;

Discussion
As a species of conservation concern, understanding the effects of competitor species on the habitat selection of ocelots is vital to management. We compared habitat selection of ocelots, bobcats and coyotes and examined if ocelots spatially avoided these competitors across two orders of selection. By leveraging landscape-level and LiDAR data we were able to take an unprecedented examination of fine-scale habitat selection by these sympatric carnivores, providing new insights and confirming observations in prior studies. At the broader level (2nd order), we observed overlap between species and no avoidance of competitors by ocelots. At a finer scale www.nature.com/scientificreports/ (3rd order), we observed fine-scale habitat partitioning that may reflect interspecific niche partitioning or be a result of competition for spatial resources. Further, we observed avoidance of coyotes by ocelots at the 3rd order, further emphasizing niche partitioning between species and revealing scale-dependent patterns in avoidance of competitor species. At a broader scale, bobcats positioned their home ranges in areas with larger patches of woody, bare and herbaceous cover types suggesting a preference for heterogeneous landscapes that were comprised of all three cover types. Bobcats selected greater herbaceous edge density and higher woody patch density, suggesting a preference for vegetation cover and interspersion of cover types, supported by our results of 3rd order habitat selection. Within their home ranges, bobcats selected areas near dense vegetation cover and open areas, further supporting a generalist pattern and selection for edges, consistent with past literature suggesting generalist habitat use 59,60 . Our results suggest selection for multiple cover types and edges across both scales examined. Prior assessments of habitat selection by bobcats have shown differences in selection across scale and stress the importance of comparing patterns at both a broad and fine scale 51,61-63 . Bobcats in southeastern United States selected croplands at a fine scale but selected pine and hardwood habitat at a broader scale 63,64 . Gene flow in a www.nature.com/scientificreports/ population of bobcats was influenced differently by cover type across varying spatial scale 51 . Bobcats avoided high elevations and heavy snow at a broad scale and selected for forest, shrub and wetland at a finer scale 62 . These prior studies show scale-dependent differences in habitat selection, however, we show similar patterns at both the 2nd and 3rd order wherein bobcats selected for edges and an interspersion of multiple cover types. Coyotes selected a broad range of cover types with fragmented patches and areas close to edges across scales; however, we observed selection for vegetated areas at the 2nd order and use of open herbaceous areas at the 3rd order (Fig. 4). In the western United States, coyotes showed consistent selection across the 2nd and 3rd order, showing a preference for early successional vegetation 65 . Chamberlain 66 similarly found selection for a variety of cover types; however, they observed seasonal differences across scale but found consistent selection for pine stands in the winter. At a broad scale, coyotes selected open vegetation types and recently burned forests while at finer scales they avoided dense vegetation and paved roads 67 . We found similar patterns between coyotes and bobcats, showing selection for all three cover types with heavy interspersion, suggesting a high degree of overlap between home ranges of bobcats and coyotes. This is consistent with long-term camera trapping data of the study area, which showed these species were up to six times more likely to co-occur in the same areas 32 . This high extent of overlap suggests these two species are not avoiding each other at the broad scale, either due to a lack of competition or due to partitioning the landscape at a finer spatial or temporal scale 31 . We did find some evidence of partitioning at the finer scale. While both species selected areas closer to dense vegetation cover and open areas, bobcats selected greater canopy cover while coyotes showed no relationship and showed much greater use of open areas than bobcats and ocelots (Figs. 3, 4 and 5). Past literature on competition between coyotes and bobcats is equivocal. Some studies have found a high degree of overlap in habitat selection and home ranges while others have not, however, in most cases co-existence is attributed to fine-scale habitat partitioning between species 38,39,68,69 , similar to our findings on bobcats and coyotes.
When positioning their home range, ocelots selected areas for greater woody and herbaceous cover, with larger woody patches and less bare ground consistent with recent studies that used landscape metrics to describe ocelot selection or use. Ocelots selected large, contiguous patches 20,21,27,30,70 with lower edge densities 30,71 across their geographic range. Larger areas of herbaceous vegetation within home ranges may also help facilitate movement when patrolling territory 31 or establishing den sites 50 . Our results also contrast Jackson et al. 72 which showed selection for fragmented areas (i.e. large patches with higher shape indices) in a smaller subpopulation of ocelots located 30 km south of our study area. At the 2nd order, ocelots selected for areas of greater probability of use by bobcats and showed no effect associated with probability of coyotes, suggesting ocelots were not avoiding Table 2. Parameter estimates from the top model, according to AICc, describing 2nd habitat selection of bobcats (Lynx rufus), coyotes (Canis latrans) and ocelots (Leopardus pardalis) in South Texas USA from 2017 to 2021. Variables include percent land cover (PLAN; %), edge density (ED; m/ha), patch density (PD; patches/100 ha), landscape shape index (LSI), and mean patch area (MPA; ha) for three cover types (bare, herbaceous, and woody cover), as well as probability of bobcat and coyote 2nd order use in the case of ocelot habitat selection. All variables in the models were scaled and centered. www.nature.com/scientificreports/ either species at the broader scale. Similarly, Lombardi et al. 32 found that ocelots were 10-12 times more likely to occur in areas occupied by coyotes and bobcats based on long-term camera trapping data. This overlap in resources may be driven by behavioral-mediated co-occurrence of activity patterns and finer scale partitioning of cover 31 which allowed each species to coexist even when there may be competition when selecting areas for home ranges. Horne et al. 26 similarly found overlap in the positioning of home ranges by bobcats and ocelots and a prior study comparing home range placement of ocelots with two other sympatric carnivores, ring-tailed coatis (Nasua nasua) and crab-eating foxes (Cerdocyon thous), similarly found overlap in home range placement among species 73 . At the 3rd order, ocelots selected areas closer to dense vegetation cover, consistent across scales, which support results from prior literature and similar to bobcats and coyotes, suggesting a possibility of interspecific competition for dense vegetation communities. Selection between ocelots and coyotes suggested less overlap, similar to the comparison between bobcats and coyotes. We observed a negative relationship between ocelots and patch www.nature.com/scientificreports/ area and vegetation density, which would partially contradict prior understanding 70 however, these differences may also be a result of variation in individual selection or selection of different canopy characteristics 74 . Within their home ranges, ocelots selected areas with a higher probability of use by bobcats at the 2nd and 3rd order, suggesting they were neither avoiding bobcat home ranges nor areas used by bobcats at a finer scale. While we saw no avoidance of coyotes at the 2nd order, at the 3rd order ocelots avoided both coyote home ranges and areas used by coyotes within their home range showing differences in habitat selection and competitor avoidance across scales. Reasons why ocelots are directly avoiding coyotes only at the third order and not 2nd order are unclear; avoidance may be the result of mutual avoidance or interspecific competition, wherein the presence of coyotes is directly influencing habitat selection of ocelots. These interactions may also be an artifact of niche partitioning or temporal segregation between species, reflecting real differences in ecological niches. Further research would be required to support one hypothesis over the other and would require examination of avoidance by coyotes or a comparison of habitat use by ocelots before and after coyote removal to identify an explanation. www.nature.com/scientificreports/ Comparisons of habitat selection between ocelots and bobcats in South Texas showed overlap in position of home ranges, consistent with our results, and found evidence of fine-scale habitat partitioning as a means of coexistence 26 , although our results showed very similar selection between bobcats and ocelots at the finescale. Dietary overlap between these two species is similar but enough variation exist to reduce some degree of competition 42 . To our knowledge, only two studies have examined coexistence between ocelots, bobcats, and coyotes in a single study and they examined presence using camera traps 32 , and hidden Markov movement models to examine behavioral differences in resource selection 31 , as opposed to multiscale habitat selection as in the case of our study. Further, prior understanding of the habitat selection of ocelots have also come from either camera traps 16,20,73,75 or telemetry 19,[25][26][27]72 . Our study benefitted from the use of high-frequency GPS data collected from all three species examined, providing a more in-depth understanding of habitat selection and potential avoidance between species.
Our study is the first to examine avoidance of functionally similar carnivores by ocelots; however, coexistence among carnivores has been examined in other portions of the ocelot's range. In South America, where bobcats and coyotes are absent, ocelots coexist with larger, more dominant predators such pumas (Puma concolor) and jaguar (Panthera onca) and were positively associated with the presence of these larger predators [35][36][37] , suggesting no negative top-down effects from these larger felids on ocelots. Within these regions, coexistence of ocelots with jaguars and pumas was attributed to temporal and spatial partitioning 35,76,77 . While larger predators did not negatively influence the presence, the diet of ocelots shifted to larger prey species in the absence of more dominant predators 78 , suggesting competition influences the realized niche of ocelots; a process that may be occurring within our study area as a result of competition from coyotes. Alternatively, as jaguars did exist within this study historically, predator release may be acting on coyotes, in the absence of jaguars, allowing them to act as more dominant predators. Ocelots did not avoid sympatric felids in Brazil but avoided domestic dogs 79 , similar to the avoidance of a sympatric canid and lack of avoidance of other felids that we observed in our study, although niche partitioning was higher among morphologically similar carnivores in Argentina 36 . Conversely, ocelots had a negative influence on the habitat use and activity of smaller felids and other mesocarnivores 35,36,80 , suggesting the potential for a similar dynamic within our study region wherein ocelots have a negative influence on coyotes through competition, potentially resulting in the habitat partitioning we observed in our study. Coexistence among sympatric carnivores has been attributed to spatial heterogeneity 81,82 and we similarly provide evidence of spatial partitioning within a heterogeneous landscape as an explanation for coexistence among ocelots, bobcats and coyotes. Our results expand upon previous literature on the coexistence of ocelots with dominant and subordinate predators by describing patterns of avoidance with predators of a similar trophic level.
In addition to the inferences drawn about habitat selection of these three carnivores and patterns of coexistence and avoidance by ocelots, our study provides another example of the importance of scale in ecological research. Habitat selection is a dynamic process that occurs across multiple scales simultaneously 1 . We therefore Table 3. AICc model selection describing 3rd order selection of bobcats (Lynx rufus), coyotes (Canis latrans) and ocelots (Leopardus pardalis) in South Texas, USA from 2017 to 2021. Top 5 models out of 12 candidate models are shown (8 in the case of ocelots). Variables include distance to dense cover (> 75% canopy cover; DistHeavyCover), distance to low cover/open areas (< 25% canopy cover, DistLowCover), patch area of dense cover (Patch Area, m 2 ), percent canopy cover (CanopyCover) and vegetation density (Veg density; vegetation points/cell), as well as probability of bobcat and coyote 2nd order use and probability of bobcat and coyote 3rd order use in the case of ocelot habitat selection.All models included animal ID as a random effect. All variables in the models were scaled and centered. www.nature.com/scientificreports/ coyotes at any scale (i.e. transmutability). In addition to scale-effects, some differences we observed may have been related to a small sample size. The concept of scale has become increasingly important in studies examining habitat selection. Recent studies have considered selection across multiple scales and shown differences across scales 3,13,14,83 . A multiscale approach has been applied to ocelots twice before 26,73 , however, the use of highfrequency GPS data in our analysis allows for a deeper level of inference over radio telemetry and emphasizes greater selection for herbaceous cover at the broad scale and scale dependent habitat partitioning and avoidance of competitor species. We recommend that, whenever possible, studies consider habitat selection across multiple scales to identify scale-dependent trends. We provide the first comparison of habitat selection of ocelots, bobcats and coyotes and compare selection across two orders (2nd and 3rd) and examine avoidance of competitor species by the endangered ocelot. We show that fine-scale habitat partitioning is occurring to facilitate coexistence between species, whereby bobcats and coyotes showed selection for a wide range of cover types and use of open areas by coyotes while ocelots were strongly tied to dense (woody and herbaceous) vegetation. We found no avoidance of competitor species by ocelots at the 2nd order, suggesting similar habitat requirements among species at the broader scale. At the 3rd order, however, we detected avoidance of coyotes but not bobcats, showing differing patterns of avoidance across scale and species. Avoidance of coyotes may reflect a competition for space between species or may simply reflect differences in ecological niche between species, thereby reducing competition. The high degree of overlap with bobcats, particularly at the fine-scale, may alternatively be a source of interspecific competition for ocelots, as these species may compete for optimal patches. Our results provide a guideline for landscape management and emphasize the importance of woody and herbaceous cover at the landscape level and patches of dense vegetation at the home-range level to sustain populations of ocelots. Further, in considering areas for reintroduction of ocelots, we provide an initial analysis to examine the impact of competitor species on ocelots. Future research may be conducted to experimentally exclude competitors to compare habitat selection of ocelots or, alternatively, examine interspecific avoidance by bobcats or coyotes to better elucidate directionality of potential competition. As a species of conservation concern, understanding the habitat selection of ocelots and the role of competitor species in influencing habitat selection is of vital importance to conserving ocelots in South Texas. Table 4. Parameter estimates from the top model, according to AICc, describing 3rd habitat selection of bobcats (Lynx rufus), coyotes (Canis latrans) and ocelots (Leopardus pardalis) in South Texas USA from 2017 to 2021. Variables include distance to dense cover (> 75% canopy cover; DistHeavyCover), distance to low cover/open areas (< 25% canopy cover, DistLowCover), patch area of dense cover (Patch Area, m 2 ), percent canopy cover (CanopyCover) and vegetation density (Veg Density; vegetation points/cell), as well as probability of bobcat and coyote 2nd order use and probability of bobcat and coyote 3rd order use in the case of ocelot habitat selection. All variables in the models were standardized.